The first dataset for which we evaluated the proposed loss function is the Indiana dataset [1]} that contains CXR scans depicting cardiac hypertrophy, pulmonary edema, opacity, and pleural effusion. The classification performance of the \(L_{IL}\)  driven classification models is reported in Table REF  where we can see that the best performance is achieved for ResNet101 [2]}. Also, it should be noted that the performance of the incremental ResNet101 model is competitive with its fine-tuning variant, i.e., the performance of incremental ResNet101 model only lags by 10.60% in terms of accuracy with the fine-tuning approach.
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